Fetching the paper…
Reading the bibliography…
Poisoning efficiency is crucial in poisoning-based backdoor attacks, as attackers aim to minimize the number of poisoning samples while maximizing attack efficacy.
Margin based active learning
Maria-Florina Balcan, Andrei Broder, and Tong Zhang · 2007
Earlier work this paper cites.
Two faces of active learning
Sanjoy Dasgupta · 2011
Earlier work this paper cites.
Poisoning attacks against support vector machines
Battista Biggio, Blaine Nelson, and Pavel Laskov · 2012
Earlier work this paper cites.
Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Identity mappings in deep residual networks
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Targeted backdoor attacks on deep learning systems using data poisoning
Xinyun Chen, Chang Liu, Bo Li, Kimberly Lu, and Dawn Song · 2017
Earlier work this paper cites.
Trojaning attack on neural networks
Yingqi Liu, Shiqing Ma, Yousra Aafer, Wen-Chuan Lee, Juan Zhai, Weihang Wang, and Xiangyu Zhang · 2017
Earlier work this paper cites.
Universal adversarial perturbations
Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, Omar Fawzi, and Pascal Frossard · 2017
Earlier work this paper cites.
Wild patterns: Ten years after the rise of adversarial machine learning
Battista Biggio and Fabio Roli · 2018
Earlier work this paper cites.
Neural tangent kernel: Convergence and generalization in neural networks
Arthur Jacot, Franck Gabriel, and Clément Hongler · 2018
Earlier work this paper cites.
Backdoor embedding in convolutional neural network models via invisible perturbation
Cong Liao, Haoti Zhong, Anna Squicciarini, Sencun Zhu, and David Miller · 2018
Earlier work this paper cites.
Fine-pruning: Defending against backdooring attacks on deep neural networks
Kang Liu, Brendan Dolan-Gavitt, and Siddharth Garg · 2018
Earlier work this paper cites.
Strip: A defence against trojan attacks on deep neural networks
Yansong Gao, Change Xu, Derui Wang, Shiping Chen, Damith C Ranasinghe, and Surya Nepal · 2019
Earlier work this paper cites.
Badnets: Evaluating backdooring attacks on deep neural networks
Tianyu Gu, Kang Liu, Brendan Dolan-Gavitt, and Siddharth Garg · 2019
Earlier work this paper cites.
Terminal brain damage: Exposing the graceless degradation in deep neural networks under hardware fault attacks
Sanghyun Hong, Pietro Frigo, Yiğitcan Kaya, Cristiano Giuffrida, and Tudor Dumitraș · 2019
Earlier work this paper cites.
Label-consistent backdoor attacks
Alexander Turner, Dimitris Tsipras, and Aleksander Madry · 2019
Earlier work this paper cites.
Cryptonn: Training neural networks over encrypted data
Runhua Xu, James BD Joshi, and Chao Li · 2019
Earlier work this paper cites.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
Earlier work this paper cites.
Invisible backdoor attacks on deep neural networks via steganography and regularization
Shaofeng Li, Minhui Xue, Benjamin Zi Hao Zhao, Haojin Zhu, and Xinpeng Zhang · 2020
Earlier work this paper cites.
Reflection backdoor: A natural backdoor attack on deep neural networks
Yunfei Liu, Xingjun Ma, James Bailey, and Feng Lu · 2020
Earlier work this paper cites.
Poisoning attacks on federated learning-based iot intrusion detection system
Thien Duc Nguyen, Phillip Rieger, Markus Miettinen, and Ahmad-Reza Sadeghi · 2020
Earlier work this paper cites.
Tbt: Targeted neural network attack with bit trojan
Adnan Siraj Rakin, Zhezhi He, and Deliang Fan · 2020
Earlier work this paper cites.
Backdoors in neural models of source code
Goutham Ramakrishnan and Aws Albarghouthi · 2020
Earlier work this paper cites.
Active sentence learning by adversarial uncertainty sampling in discrete space
Dongyu Ru, Jiangtao Feng, Lin Qiu, Hao Zhou, Mingxuan Wang, Weinan Zhang, Yong Yu, and Lei Li · 2020
Earlier work this paper cites.
Backdoor attacks against transfer learning with pre-trained deep learning models
Shuo Wang, Surya Nepal, Carsten Rudolph, Marthie Grobler, Shangyu Chen, and Tianle Chen · 2020
Earlier work this paper cites.
Cold-start active learning through self-supervised language modeling
Michelle Yuan, Hsuan-Tien Lin, and Jordan Boyd-Graber · 2020
Cited alongside, same era.
Clean-label backdoor attacks on video recognition models
Shihao Zhao, Xingjun Ma, Xiang Zheng, James Bailey, Jingjing Chen, and Yu-Gang Jiang · 2020
Cited alongside, same era.
Backdoor embedding in convolutional neural network models via invisible perturbation
Haoti Zhong, Cong Liao, Anna Cinzia Squicciarini, Sencun Zhu, and David Miller · 2020
Cited alongside, same era.
Blind backdoors in deep learning models
Eugene Bagdasaryan and Vitaly Shmatikov · 2021
Cited alongside, same era.
Deep feature space trojan attack of neural networks by controlled detoxification
Siyuan Cheng, Yingqi Liu, Shiqing Ma, and Xiangyu Zhang · 2021
Cited alongside, same era.
Data-efficient backdoor attacks
Pengfei Xia, Ziqiang Li, Wei Zhang, and Bin Li · 2022
Later among the works it cites.
Enhancing backdoor attacks with multi-level mmd regularization
Pengfei Xia, Hongjing Niu, Ziqiang Li, and Bin Li · 2022
Later among the works it cites.
Post-training detection of backdoor attacks for two-class and multi-attack scenarios
Zhen Xiang, David J Miller, and George Kesidis · 2022
Later among the works it cites.
Not all poisons are created equal: Robust training against data poisoning
Yu Yang, Tian Yu Liu, and Baharan Mirzasoleiman · 2022
Later among the works it cites.
Narcissus: A practical clean-label backdoor attack with limited information
Yi Zeng, Minzhou Pan, Hoang Anh Just, Lingjuan Lyu, Meikang Qiu, and Ruoxi Jia · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Backdoor attack with imperceptible input and latent modification
Khoa Doan, Yingjie Lao, and Ping Li · 2021
Cited alongside, same era.
Black-box detection of backdoor attacks with limited information and data
Yinpeng Dong, Xiao Yang, Zhijie Deng, Tianyu Pang, Zihao Xiao, Hang Su, and Jun Zhu · 2021
Cited alongside, same era.
Anti-distillation backdoor attacks: Backdoors can really survive in knowledge distillation
Yunjie Ge, Qian Wang, Baolin Zheng, Xinlu Zhuang, Qi Li, Chao Shen, and Cong Wang · 2021
Cited alongside, same era.
Aeva: Black-box backdoor detection using adversarial extreme value analysis
Junfeng Guo, Ang Li, and Cong Liu · 2021
Cited alongside, same era.
Spectre: defending against backdoor attacks using robust statistics
Jonathan Hayase, Weihao Kong, Raghav Somani, and Sewoong Oh · 2021
Cited alongside, same era.
Backdoor attack on machine learning based android malware detectors
Chaoran Li, Xiao Chen, Derui Wang, Sheng Wen, Muhammad Ejaz Ahmed, Seyit Camtepe, and Yang Xiang · 2021
Cited alongside, same era.
Invisible backdoor attack with sample-specific triggers
Yuezun Li, Yiming Li, Baoyuan Wu, Longkang Li, Ran He, and Siwei Lyu · 2021
Cited alongside, same era.
Wild patterns reloaded: A survey of machine learning security against training data poisoning
Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis, Sebastiano Vascon, Werner Zellinger, Bernhard A Moser, Alina Oprea, Battista Biggio, Marcello Pelillo, and Fabio Roli · 2023
Closest in time.
Not all samples are born equal: Towards effective clean-label backdoor attacks
Yinghua Gao, Yiming Li, Linghui Zhu, Dongxian Wu, Yong Jiang, and Shu-Tao Xia · 2023
Closest in time.
Junfeng Guo, Yiming Li, Xun Chen, Hanqing Guo, Lichao Sun, and Cong Liu · 2023
Closest in time.
Domain watermark: Effective and harmless dataset copyright protection is closed at hand
Junfeng Guo, Yiming Li, Lixu Wang, Shu-Tao Xia, Heng Huang, Cong Liu, and Bo Li · 2023
Closest in time.
A temporal chrominance trigger for clean-label backdoor attack against anti-spoof rebroadcast detection
Wei Guo, Benedetta Tondi, and Mauro Barni · 2023
Closest in time.
Towards sample-specific backdoor attack with clean labels via attribute trigger
Yiming Li, Mingyan Zhu, Junfeng Guo, Tao Wei, Shu-Tao Xia, and Zhan Qin · 2023
Closest in time.
Black-box dataset ownership verification via backdoor watermarking
Yiming Li, Mingyan Zhu, Xue Yang, Yong Jiang, Tao Wei, and Shu-Tao Xia · 2023
Closest in time.
A systematic survey of regularization and normalization in gans
Ziqiang Li, Muhammad Usman, Rentuo Tao, Pengfei Xia, Chaoyue Wang, Huanhuan Chen, and Bin Li · 2023
Closest in time.
Explore the effect of data selection on poison efficiency in backdoor attacks
Ziqiang Li, Pengfei Xia, Hong Sun, Yueqi Zeng, Wei Zhang, and Bin Li · 2023
Closest in time.
Towards stable backdoor purification through feature shift tuning
Rui Min, Zeyu Qin, Li Shen, and Minhao Cheng · 2023
Closest in time.
Real is not true: Backdoor attacks against deepfake detection
Hong Sun, Ziqiang Li, Lei Liu, and Bin Li · 2023
Closest in time.
Computation and data efficient backdoor attacks
Yutong Wu, Xingshuo Han, Han Qiu, and Tianwei Zhang · 2023
Closest in time.
Batt: Backdoor attack with transformation-based triggers
Tong Xu, Yiming Li, Yong Jiang, and Shu-Tao Xia · 2023
Closest in time.
Efficient trigger word insertion
Yueqi Zeng, Ziqiang Li, Pengfei Xia, Lei Liu, and Bin Li · 2023
Closest in time.
Ibd-psc: Input-level backdoor detection via parameter-oriented scaling consistency
Linshan Hou, Ruili Feng, Zhongyun Hua, Wei Luo, Leo Yu Zhang, and Yiming Li · 2024
Closest in time.
Nearest is not dearest: Towards practical defense against quantization-conditioned backdoor attacks
Boheng Li, Yishuo Cai, Haowei Li, Feng Xue, Zhifeng Li, and Yiming Li · 2024
Closest in time.
Efficient backdoor attacks for deep neural networks in real-world scenarios
Ziqiang Li, Hong Sun, Pengfei Xia, Heng Li, Beihao Xia, Yi Wu, and Bin Li · 2024
Closest in time.
Large language models are good attackers: Efficient and stealthy textual backdoor attacks, 2024
Ziqiang Li, Yueqi Zeng, Pengfei Xia, Lei Liu, Zhangjie Fu, and Bin Li · 2024
Closest in time.
Backdoorbench: A comprehensive benchmark and analysis of backdoor learning
Baoyuan Wu, Hongrui Chen, Mingda Zhang, Zihao Zhu, Shaokui Wei, Danni Yuan, Mingli Zhu, Ruotong Wang, Li Liu, and Chao Shen · 2024
Closest in time.
Towards faithful xai evaluation via generalization-limited backdoor watermark
Mengxi Ya, Yiming Li, Tao Dai, Bin Wang, Yong Jiang, and Shu-Tao Xia · 2024
Closest in time.